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The impact of the development of music streaming services on Czech radio stations
Šidlák, Jan ; Klabíková Rábová, Tereza (advisor) ; Moravcová, Hana (referee)
This bachelor thesis deals with the topic of the transformation of communication of Czech radio stations in the light of the development of streaming platforms, new media and technologies. In particular, it describes how radio stations use new media to communicate and complement traditional FM broadcasting. The theoretical part of the thesis describes the history of radio in our country, introduces streaming services as a new way of music distribution and summarizes the views of some authors who have dealt with the topic before. The practical part of the thesis consists of an analysis of media outputs of individual stations and interviews with respondents, professionals from radio practice.
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Analysis of documentary production of the online streaming service Netflix
Spěváková, Klára ; Štoll, Martin (advisor) ; Kruml, Milan (referee)
This thesis, titled Analysis of the Documentary Production of the Online Streaming Service Netflix, aims to describe the characteristics typical of Netflix's documentary production using a selection of films from 2015 to 2022. The films included in the analysis are American Murder: The Family Next Door, Schumacher, The Social Dilemma, The Tinder Swindler and David Attenborough: A Life on Our Planet. Based on semiotic and image analysis, it examines the various elements of film language used in these films - mise-en-scene, camera, editing and sound, including the narrative mode and structure of the film. The thesis also focuses on describing the key features of Netflix production, its use to influence audiences, and the search for the reason behind the popularity of this production. The thesis also includes a quantitative analysis of Netflix's documentary production.
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Impacts of the COVID-19 pandemic on streaming services and their users
Měska, Tomáš ; Kruml, Milan (advisor) ; Štoll, Martin (referee)
This thesis examines the impacts of the COVID-19 pandemic on streaming services and their users. It aims to shed light on how the impacts of the coronavirus pandemic, as well as the government measures and lockdowns that stifled social life and locked people in their homes for weeks, affected the use of streaming platforms by their users. This thesis focuses on the main characteristics and types of streaming services, the basic concepts associated with them, and looks at the production of new content as well as their distribution models. The subsequent section discusses the coronavirus and its impact on social behaviour, and then in particular the impact on the film industry in terms of production, content, cinema and film festival operations and of course the streaming services themselves. The final segment of the thesis then analyses and interprets the data collected in the questionnaire survey. Respondents' answers provide the basis for finding solutions to the research questions, which identify which streaming services users use, how many they use concurrently, how much time they spend watching streaming content, what categories of content they watch, or in what ways they use the services, for example in terms of devices or in comparison to other types of media.
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Strategy of the Netflix platform and habits of content consumption of users in the Czech Republic
Rajnohová, Dominika ; Švelch, Jaroslav (advisor) ; Reifová, Irena (referee)
This diploma thesis deals with the topic of video on demand platforms and is more closely focused on one of the main worldwide available platform managed by Netflix. The thesis describes the history of the service and the basic principles and theories on the basis of which this service works. Attention is devoted to the functioning of this platform in the Czech Republic and the development of the user interface and expansion of the catalogue in order to gain more attention from the Czech audience. The research part of the thesis provides insights into the way how the platform is used by Czech users, specifically among 20-27 years old students. The qualitative survey examined the period and ways of how Netflix became known among the users, how users gained access to video content before subscribing Netflix and how the platform influenced their series and movie consumption habits. The research also focused on the perception of the offered content, on the form and price of the subscription and on the user-friendliness and functionality of the platform. The other aim of the research was to find out how much time users spend watching movies and series and in which situations they are looking for this activity. Part of the research also looked at changes in the use of the streaming service during the...
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The coronavirus epidemic and the audience of Mall.tv
Pokorná, Jana ; Miessler, Jan (advisor) ; Hodboď, Vojtěch (referee)
This thesis is investigating the question of how and why there was a change in a viewership of the internet television Mall.tv during the first wave of the coronavirus pandemic in spring 2020. While looking for an answer for this work, a quantitative analysis of internal data provided by Mall.tv is used. This all is processed with the help of statistical methods. Simultaneously, this work is testing the hypothesis, according to which the audience show #kulturažije could be the key factor influencing the transformation of the size and socio demographic composition. From the results of the analysis, it is clear that the audience was not changed during the spring and that major changes are visible after the spring wave. The hypothesis, which states that the show #kulturažije was supposed to bring more new users to the website, was not confirmed but it was found that impact of the project was rather marginal.
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Predicting the Behaviour of Streaming Services Users
Stachura, Šimon ; Pilát, Martin (advisor) ; Peška, Ladislav (referee)
Title: Predicting the Behaviour of Streaming Services Users Autor: Bc. Šimon Stachura Department: Katedra teoretické informatiky a matematické logiky Supervisor: Mgr. Martin Pilát, Ph. D. Abstract: Streaming services are one of the phenomena of the last decade, allowing online legal access to media for a large number of users. The media is usually provided to the users as an automatically generated sequence, created by some form of a recommender system. The preferences of individual users are usually estimated based on historical data from their previous usage of the service. Skipping behaviour on individual elements of the generated sequence (songs, for instance) is one of the basic signals expressing these preferences. Goal of this work is to predict users' behaviour based on their previous experience with the service. We chose a large dataset consisting of real data from usage of the Spotify service, and considered options for preprocessing and representing them. We decided to use recurrent neural networks with the Encoder-Decoder architecture for modelling the behaviour of the users. These models encode the information about users' historical behaviour into a compact inner representation of the session, and based on that representation they generate expected behaviour in the next time steps. We created...
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